• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Information Systems Review
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• v.13 no.1
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• pp.75-96
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• 2011

This research uses coolhunting to predict the future trend of e-Commerce industry. Coolhunting is a method to take Cool Trends which are the future trend through social network analysis for discovering the trendsetter and its collective intelligence. Coolhunting is generally carried out by social network analysis while this research uses NodeXL of social network analysis tools. We designed industrial network research model for relation among e-Commerce corporation, product, the types of customer service and customer service employee to discover the Cool Trends of e-Commerce industry. According to the result of this research, e-Commerce industrial network was being changed from chaos to collective intelligence form. As a analysis result for network influences, we found that Cool Trends of e-Commerce industry invigorate social commerce industry through the collective intelligence focusing intelligence VIP, Excellence, grade of Administrating for women customers(trendsetter) and it promotes semantic consumption from customers and purchasing power will be concentrated on cosmetic, beauty, perfume product categories in social commerce. We propose the strategic direction for e-Commerce corporation and hope that domestic e-Commerce corporation continues to grow and high-quality services are provided for customers.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.308-318
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• 2017

The purpose of this study was to investigate the influence of the leadership of the top-leader and the mid-level leader on the care burden of care workers. A survey was conducted on 400 care workers working in long-term care facilities in Seoul and Gyeonggi area. We conducted a hierarchical regression analysis to grasp the effect of the leadership of top-leader and mid-level leader on the care burden of care workers. Monthly income of care workers was significantly associated with care burden. In next step, the leadership of the top-leader affected the care burden of care workers. But, In last model 3, only the leadership of mid-level leader affected the care burden with monthly income. This findings suggested that it is urgent to stabilize the salary level of care workers, and to develop the leadership skills of mid-level leader. The improved leadership of Mid-level Leader will help to reduce jop chaos for care workers.

• Journal of Korean Medical classics
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• v.21 no.4
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• pp.75-83
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• 2008

Based on the sentence "The number of my family member and relatives reached around 200, but since the first year of Geonan(建安) era, two thirds of them died and seven out of ten died of cold damage in less than ten years" in Sanghanjapbyeongron(Treatise on Cold Damage and Miscellaneous Diseases), which is allegedly known to be written by Jangnunggyeong(張仲景), we analyzed the sentence by three factors of time, location and people. These factors are used in the investigation of the disease outbreak, and through this analysis, following conclusions were made. 1. Approximate 10 year crude mortality rate since A.D 196(the first yea of Geonan era) in Jangsa(長沙) province was 67 out of 100 in the population. Approximate 10 year disease-specific mortality rate of cold damage since A.D 196(the first yea of Geonan era) in Jangsa(長沙) province was 47 out of 100 in the population. Regardless of age, gender or other demographic variables, approximate 10 year proportionate mortality ratio since A.D 196(the first yea of Geonan era) in Jangsa province was 70.2%, which lead to the assumption that 70% of death is cold-damage related. 2. Increased disease-specific mortality rate by cold damage in Jangsa(長沙) province for about 10 years since A.D 196(the first yea of Geonan era), and followed increased crude mortality rate in the population, threatened the stability of nation or local government. This is due to the repeated war in late Han Dynasty with political chaos and repeated flood caused by geographical disadvantage in Jangsa province.

• Nutrition Research and Practice
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• v.3 no.3
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• pp.226-233
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• 2009

Traditional nutrition education has not been shown to consistently produce behavior change. While it has been suggested that using emotion-based messages may be a better way to influence nutrition behavior change, this has not been well tested. Producing emotion-based messages is a multi-step process that begins with exploring subconscious barriers to behavior change rather than the more obvious and typically reported barriers. The purpose of this research was to uncover the emotional reasons, sometimes referred to as emotional pulse points, for mothers' choosing or not choosing to have more family meals. This would then serve as the first step to developing emotion-based messages promoting the benefits of family meals. Five focus group interviews were conducted with 51 low-income Black (n=28) and white (n=23) mothers. Metaphorical techniques were used to determine underlying feelings toward family and family meals. Discussions were video-taped, transcribed, and manually analyzed using a content-driven, immersion/crystallization approach to qualitative data analysis. Four themes emerged around the definition of family: acceptance, sharing, chaos, and protective/loyal. Some mothers felt mealtime was merely obligatory, and described it as stressful. Some reported a preference for attending to their own needs instead of sitting down with their children, while others felt that mealtime should be used to interact with and educate children and felt guilty when they were not able to provide family meals. Three themes emerged around feelings towards having or not having family meals: unimportant, important, and guilty. When explored further, mothers indicated that using the feeling of guilt to encourage family meals might be effective. Data obtained are being used to develop innovative, emotion-based messages that will be tested for effectiveness in promoting family meals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.910-913
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• 2007

Information society, introduced by the rapid progress of computer technology and communication technology, has brought us the comfort and prosperity on every aspect of human life. However, the adverse and harmful effects of it, including the ethics problems, turn out to be serious. Concerning these problems, purpose of this study is set to investigate the actual state of ethics awareness on information and communication, since ethics awareness is required more urgently than ever in this era of technology. While adolescents, who will lead the future society, comprise the majority of internet usage population in our nation, they are exposed to the harmful and risky contents in the periods during which their world view would be established. Furthermore, the problems emerging in the progress towards information-oriented society are jeopardizing the dignity and inherent value of human being, therefore causing the serious moral chaos and social problems. In this paper, the awareness level of middle school students in Gwangju City has been investigated especially in the aspect of information and communication. Based on the results, it is revealed that the efforts of government, social organization, students' parents as well as the education circles are essential. Also the proposal for improvement on the awareness level has been presented.

• Smart Structures and Systems
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• v.14 no.3
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• pp.327-345
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• 2014

This paper presents a composite control strategy for the active suppression of vibration due to the unknown disturbances, such as external excitation, harmonic effects and control spillover, as well as high-frequency accelerometer measurement noise in the all-clamped stiffened plate. The proposed composite control action based on the modal approach, consists of two contributions including feedback part and feedforward part. The feedback part is the well-known PID controller, which is widely used to increase the structure damping and improve its dynamic performance close to the resonance frequencies. In order to get better performance for vibration suppression, the weight matrixes is optimized by chaos sequence. Then an improved disturbance observer (IDOB) as the feedforward compensation part is developed to enhance the vibration suppression performance of PID under various disturbances and uncertainties. The proposed IDOB can simultaneously estimate the various disturbances dynamically as well as measurement noise acting on the system and suppress them by feedforward compensation design. A rigorous analysis is also given to show why the IDOB can effectively suppress the unknown disturbances and measurement noise. In order to verify the proposed composite control algorithm (IDOB-PID), the dSPACE real-time simulation platform is used and an experimental platform for the all-clamped stiffened plate active vibration control system is set up. The experimental results demonstrate the effectiveness, practicality and strong anti-disturbances ability of the proposed control strategy.

• Journal of Korean Academy of Nursing
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• v.36 no.5
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• pp.782-791
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• 2006

Purpose: The purpose of this study was to conceptualize and clarify a concept of "preparatory grief" in terminal cancer patients. Method: A hybrid model of concept development was applied to develop a concept of preparatory grief, which included a field study carried out in Busan, Korea. Participants of this study were 8 cancer patients. Results: On the basis of our literature, research and clinical experience, the concept of preparatory grief emerged as a complex phenomenon playing an important role in five areas; physical, emotional, interpersonal, religious, and transcendental dimensions. Two new attributes were defined through a field phase; trust of the post-mortal world and a serene state of mind. Indicators reflected attitudes of sadness, worry, regret, capability to adapt and hope. The results of preparatory grief were loss of energy and interest, emotional chaos, contemplation, taciturnity and restoration. Conclusions : Differentiating among preparatory grief and other symptoms in cancer patients is essential because of therapeutic implications. Understanding preparatory grief is necessary in order to manage cancer patients for promoting quality of life so that its application may have a positive impact on the patient's life.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.461-467
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• 2002

Signals reduced from the brain had been considered as a noise that is caused by the stochastic process until 1980. The recent non-linear dynamic theory researches, however, reported that these signals are meaningful and deterministic chaos signals in which they show how the brain deals with various information Since this report, a wide range of researches has been carried out and still in progress. Thus, by using the correlational dimension, one of the non-linear analytical methods, the characteristics of the brain signals can be analyzed. In this thesis, the scent of lavender, which stimulates the olfactory sense, is introduced to measure EEG with the International 10-20 electrode system on 16 channels, and to analyze the interrelationship between the original signals before the stimulation and the changed signals after the stimulation. Finally, the effect of the scent stimulation to the brain is analyzed. The purpose of this thesis is to apply these analyzed results to the computerized mapping of the brain signals and possible ways of specifying the source of the brain signals through various medical applications.